Friday, July 31, 2009

I haven't gotten a lot of public feedback on my book, but the private feedback is rather circular. On one hand, there are those saying my findings are wrong. I'm 'saying the earth is flat', in one irate economist's view. My empirical findings are not rigorous, in that I'm using incorrect statistical tests and if I used a more powerful test I would not reject the hypothesis that risk explains returns as standard theory dictates. Indeed, many of the articles I reference in my support leave open this possibility. I admit it's possible. Anything's possible. It's just improbable. The current paradigm finds parochial risk factors for each asset class (a different one for currencies, cross sectional equities, bonds), without any intuition. Further, adding more complexity to any test lessens its statistical power, and so the 'failure to reject' would give one solace if the theory kinda worked. The theory sucks, it mainly has the wrong sign (higher risk assets in any asset class, in general, have lower than average returns!)

On the other side, I get comments like 'this is obvious', it's 'too simple', or 'everyone knows that'. I too think it is obvious and simple, but not everyone in finance knows that 1) risk and return, in general, are uncorrelated in any obvious way and 2) this is an equilibrium result if people have relative status orientation. Saying something new, true, important AND obvious&simple, is better than just being new, true, and important. But the people who recognize it is obvious and true tend to be new to the literature, and so aren't trained to not see what is directly before their eyes. Experts develop special lenses to observe reality, called a 'theory', and after a while can't see without it. They are like American Natives who supposedly could not see Columbus's ships as they appeared on the horizon because their brains were hardwired to not see what is impossible.

But, the newbies look at the data I present, which is mainly a survey of the literature and sample averages, and see it as obvious (see SSRN summary of evidence here). Those who have been in the field for years see it as untrue, those who don't have it as a primary concern, think it is obvious and rather trivial. I like the future of my idea on that score, because as they say, science advances one funeral after another.

But then I noted two Amazon reviewers found it did not have any implications for your average investor. Let me try again, because obviously anyone smart enough to buy and read my book is no fool, as this is all my fault.

In the book I go into 'finding alpha' strategies, based on the fact good strategies are highly parochial, most people fail at such endeavors, and people lie about what they are doing. But the 30,000 foot practical investing implication is rather obvious: buy 'low risk' stocks, relatively. This can be done many ways: while keeping total beta at 1.0, maximizing the Sharpe ratio, or maximizing the Information Ratio. All of these are improvements relative to the S&P500 passive benchmark at orders of magnitude greater than the lift of going from active to passive equity investing. As long as the CAPM does not work, and I argue it does not because most investors are benchmarking, this implies such obvious investing tactics that basically focus on the low volatility, and avoid the high volatility. See discussion below from my videos.

Wednesday, July 29, 2009

Paul Wilmott today warns us against the scourge of computer trading, and it seems everyone has an opinion on it (see NYTimes , Trader Magazine, Chuck Schumer, Tyler Cowen). Alas, this covers such a broad umbrella of strategies, one can be against this only like one may dislike unpopular books. The panic piece begins as follows:

The idea is straightforward: Computers take information — primarily “real-time” share prices — and try to predict the next twitch in the stock market. Using an algorithmic formula, the computers can buy and sell stocks within fractions of seconds, with the bank or fund making a tiny profit on the blip of price change of each share.

This has been ongoing with Moore's law. In the bad old days orders were given to a human (called a 'specialist') who then had the ability to accept, or back away, from orders as they came in. With electronic exchanges, much of this is being done not by a priviledged specialist, but rather computers. They basically do the same thing, only now their is much more competition. Remember back in the 1990s when Harris, Christie and Schultz and reported tha Nasdaq quotes bizarrely omitted 'odd eigths'. That is, the could post a bid-ask as 3/8-1/2, but instead regularly posted 1/4-1/2. This was for many very large companies such as Microsoft and Apple, that even then traded millions of shares a day. This was collusion, and shortly after the publication of this piece these stocks magically began trading at odd eigths, though no one was ever convicted of any collusion.

Stock specialists who consolidate retail orders to buy and sell have been ripping off customers since trading began. The first head of the SEC was Joe Kennedy, who was a master stock manipulator in the 1920's. He was a master of the stock pool (bucket shop), a then-legal stunt in which a few traders conspired to inflate a stock's price, selling out just before the bubble burst. Regulation to protect the integrity of the investor invariably meant stiflying competition, allowing the big exchanges (NYSE and AMEX) to make easy money by being 'in the club'. For generations, specialists would sit on trades for minutes, not milliseconds, while they decided how to maximize their profits. I know one guy who worked for a specialist around 2000, and he noted his boss lost money only a handful of days every year. Specialists would emphasize the risk they took in providing liquidity, yet on big gap days like October 19 1987 they did not step in and exacerbated the situation. The risk they took on providing orderly markets was a license to steal for decades, and they now scream 'unfair!' as their order flow evaporates.

With electronic exchanges, the competition is much greater. Bid-ask spreads are only a penny for most S&P500 companies (as opposed to 25 cents 20 years ago), and they are generally very deep. It is rumored that Renaissance's flagship hedge fund (not the long only fund) makes most of its money as an off-the-exchange market maker. They invested a lot of money in computers, and algorithms that efficiently set bids and offers given recent order flow, the depth of the market (level 2 quotes), and their own inventory. Good for them.

There are basically three types of algorithmic trading strategies. In one, you are basically slicing a big order into littler bits to minimize trade impact. No longer do you need a human to work a 5000 share order, rather, a machine spits it into digestable chunks and by the day you are done, and don't owe anyone a big holiday basket for their hard work. In another, you basically have a machine implement relative value trades. The famous pairs trading, where if Pepsi rises, but Coke stays flat, you sell Pepsi and buy coke, is based on this idea. But it can be generalized to indices versus sectors, or baskets against each other based on statistical properties, or even oil futures vs. Exxon. Lastly, there are the market making algorithms that try to capture the spread in the market by correctly anticipating the future distribution of retail order flow based on the current book, and this strategy can complement a relative value trading algorithm. Many times these algorithms try to reverse engineer future trades via the way current trades are coming in. As many trades come in each second, for many stocks the best bids and offers are adjusted several times a second.

One article noted that some algorithms basically infer the price increase from trades, getting rid of the profits otherwise available. But these are all short term scenarios, and basically make a market efficient. That is, say Apple announces good news, suggesting a sharpe bounce in the stock. An investor tries to buy, and would like to trade 1MM shares, but clearly that's too much, so he puts in an order for 1000, then next minute, another 1000, and another. A machine might sense the pattern and basically jump on for the ride with him, diluting his profits. Is that bad news? Only for the short-term trader. For the longer run investor oblivious to this, who was on the other side, they got to sell at a higher price (the price rose faster than otherwise). The short-term speculator basically makes less because the algorithm reverse engineers his insight. This is the essence of an informationally efficient market, where news gets into the price asap. That those at the bleeding edge are making a profit is not a bug, it's a feature.

Several bloggers have made a big deal out of 'flash trading' article in Traders Magazine, where exchanges give priviledged access to order flow, letting them accept or reject these trades prior to hitting the general market. Normally this would upset me, but they have an option lasting only 30 milliseconds (30 thousandths of a second). For a computer, this is enough time to make a decision. This is certainly enough time to make a tenth of a cent or so on market orders by leaning on the existing book. That is, if the market is bid-ask at 10.03-05, with 100 shares on each, a market order to buy 100 shares might make you hit the offer at 10.05 because you know there is 100 shares following you, and you hope the price increases based on this flow. This is known as 'front running'. Or you might see more buying coming in at a limit price of 10.02, and decide to increase your bid at 10.03 because you know your downside is now limited to a penny, as you can sell at 10.02 in size. This is known as pennying a bid, because you basically use the other person's limit orders as a backstop, giving you a penny downside risk. As tendencies move probabilistically, on any one trade such shenanigans are worth much less than a penny, but it can add up for the one doing it. For your average investor, in contrast, it is totally irrelevant. In the context of buying a $20 stock, does the fact that a highly competitive group can make tenths of a cent on market transactions bother me? No. It is orders of magnitude lower than 10 years ago, which is orders of magnitude lower than 30 years ago. Commissions for most investors are at least a penny. Of all the financial skullduggery in the world today, Flash Trade front running worth a fraction of a penny is small beer.

But Wilmott paints a scary picture:

the problem with the sudden popularity of high-frequency trading is that it may increasingly destabilize the market. Hedge funds won’t necessarily care whether the increased volatility causes stocks to rise or fall, as long as they can get in and out quickly with a profit. But the rest of the economy will care.

I surmise that poor Paul has not been invited to consult on these algorithms, and like many experts, finds those excelling at something in his field of expertise is useless at best, but probably damaging. After all, if it was important and useful, he should be a player, because that's his wheelhouse, right? Of course, given the many different types of algorithms extant, it could be they glom on to some vicious positive-feedback loop, but given the profits they are chasing, these are micro-bubbles, a couple pennies. An algorithm chasing micropennies does not instigate trends the way portfolio insurance did in the 1987 crash, because in that case long-only funds were looking at their total long position, selling into declines (emulating a put option). The current algorithms generally look at relative value trades between sectors or issues, momentary order imbalances, a very different beast. Trade imbalances have always and will continue to move prices, but that isn't the computers fault. If there's continually 10x as many sell orders as buy orders, the result is going to be lower prices no matter what market is created. When buys and sells are coming in with equal size, price stability will be restored. To suggest the computers could exaggerate a movement is hysterical fear mongering in this context, because while anything is possible, it's a baseless hypothetical. Maybe we should regulate financial textbook writers as they popularize models that create things like CDO's that were so prominent in our latest financial crisis? Perhaps he is diverting our attention from his crime of the century?

Paul then concludes:

Buying stocks used to be about long-term value, doing your research and finding the company that you thought had good prospects. Maybe it had a product that you liked the look of, or perhaps a solid management team. Increasingly such real value is becoming irrelevant. The contest is now between the machines — and they’re playing games with real businesses and real people.

He is bringing up the perenial idea that investors should trade less, which I think is good practice. But earlier he suggested insiders make too much money off short term trades, implying higher trading costs. Isn't this then a disincentive to trade? So what should it be? When you propose two conflicting ideas why you are against something this reveals you aren't arguing on principle. And aren't houses the prototypical asset with high transaction costs and long investment horizons that should make them immune to bubbles? Remember, before there were maniacal machines making money in a competitive market, there was a a government-backed oligopoly or monopoly of trade execution.

Basically, people who do not understand a market where some participants are making a lot of money are often eager to call for regulation of that market because it seems obviously unfair. The solution, however, is invariably to merely entrench a status quo with a bigger shield against competition, but one where the profits can be shared equally by the exchanges, their member firms, and their regulators (through revolving door employment at the top ranks between exchanges, firms, and government). There was little 'change' on the exchanges prior to the 1990 computer revolution, and they robbed the public blind the whole time because they had a monopoly on order flow, all the while regaling their friends at the country club about their deft risk management skills and financial acumen ('the market was down and I still made money!').

Leave the market alone. It is very competitive, and if some electronic exchanges have different rules where people feel their orders are treated more fairly, volume will flock there (there are about 5 electronic exchanges). Competition is the best regulator ever invented. If you think someone making a tenth of a cent on your order is a big problem, you trade too much.

Tuesday, July 28, 2009

I'm affiliated with a company whereby I have to provide all my brokerage statement per SEC rules. This is designed so that those with inside information do not 'front run' orders in other accounts. Say I work for Fidelity (buy side), or Goldman (sell side). I have access to information that can be very profitable. This is not so much knowing the Fidelity thinks IBM is a good buy, but rather transacting a few moments prior to the much larger institutional order, or corporate action like an analyst upgrade or stock repurchase plan announcement.

My friends told me that in the 1990's, many people who worked at brokerages would routinely get in front of recommendations ('strong buy'), and this made them as much as they made from their 'day job'. Clearly, there is a strong conflict of interest, this basically robs their customers, who merely end up paying more. So, this appears a good regulation.

But consider how this is being enforced. You have regulators who get stacks of hard copy reports from various brokerage accounts for many employees. As these reports are in all different formats, there's no way to do this but to 'eyeball' thousands of pages of documents, and compare this to electronic trading records which include hundreds of thousands, if not millions, of transactions. It's like looking for a needle in a haystack. As regulators have finite resources, this prevents them for looking at other transgressions.

Now consider I wished to front run, knowingly break this law. My first obvious thing to do would be to set up an account and not tell anyone. I have several accounts. There's no national account registry to make sure I gave all of them to the SEC. How would they catch that? I don't know, but I imagine any such fraud occurs not by hoping the SEC won't match up my trades with actual orders, but rather they won't know I had another account I did not mention.

I think a better regulatory mechanism would merely be to get everyone's 1099 form that lists dividends, interest, and capital gains from each of their brokerage accounts. As the brokerages all supply them to the IRS, I can't unilaterally withhold such information without getting caught there. Only in cases where profits are large, say capital gains greater than 10% of my salary and I traded more than 10 times, should this then flag that regulators receive my transaction report from which to check against company trade records. After all, if I don't trade much, or don't make sufficient money trading, I probably was not cheating (or if I was, not enough to matter).

But think outside the box. If this is the system, one could easily outfox it: bring in a father-in-law, or a friend. The bottom line is that any system put into stone can be easily gamed if one tries hard enough. The easy fraud should be checked and made illegal. A system should be set up recognizing that resources are finite, and should not assume that a system will catch everything. The current approach relies on rule-breakers telling the truth, and that their regulators have the attention span of a an autistic looking at design specs. It is useful to check brokers personal brokerage accounts, but a simple system that can be automated would allow humans to do what they are best at, looking at funds like Madoff's with suspicious returns, and have discrete authority to audit their financials.

If you just set up rules, and then hire bureaucrats to implement mind-numbingly boring rules, that is pretty lame. But that's all we can expect out of Washington, which is why the best regulator is competition.

Monday, July 27, 2009

Josef Lakonishok and Robert Haugen wrote a book, The Incredible January Effect, in 1988. At about 110 pages, it's a quick read, and you can get a used copy on Amazon for under $10 delivered to your door (I love used books). They presented the then most prominent behavioral anomalies at that time. This highlights the problem of the behavioralists.

The book starts with an anecdote about how some bankers noticed a pattern in interest rates, and the Efficient Markets/Random Walk blinders made this impossible for these professors to see. Interest rates are low in March, high in October, a difference of about 50 basis points! Alas, this effect, I must say, I was unaware of. It certainly does not show up in the Fed's H15 data. As neither author talks about this anymore, I think this is just one of those little mistakes everyone hopes people will ignore. So I will.

Their big idea is that basically all of the 'risk premium' in stocks and bonds occurs in January. This is because institutions pick stocks then, pushing up prices of risky, and small stocks (which are risky). Over the year stock pickers stop 'buying', so stocks just meander the other 11 months of the year. Alas, most of this effect turned out to be driven by low-priced, illiquid stocks. These small stocks would move from 3/8 to 1/2, back to 3/8, and the daily cumulative return was huge, because the tapes showed +33%, -25%, +33, -25%, etc. Add to this that your retail prole got a horrible fill back in those days (this is when they invented the term 'rip your face off'), so you would actually be adversely filled, so the only one receiving the January effect where the floor traders. playing this game just generated excess trades. No one thinks the January Effect is real anymore, it was an artifact of crappy, high frequency data on a biased sample (illiquid stocks).

This same bias drove the famed Thaler and DeBondt mean-reversion trade, which conspicuously has no children in the literature (see Conrad and Kaul, 1993). To the extent their is negative autocorrelation at 36 months, it is imperceptible. In contrast, the momentum effect of Jegadeesh and Titman, which finds positive autocorrelation at 12 month horizons, is robust to excluding low-priced stocks, and has remained in the literature.

Currently people are focused on biases from excessive complexity of asset backed securities, and the spreads for all such assets has risen as they have all been tarnished by the poor performance of AAA rated mortgage-backed securities. Yet this 'bias', seems rather focused on one bad assumption, that housing prices would not fall. It really was not much more complicated than that. Regulators and the market are punishing these products. I don't see this as a big improvement, in that excessive pessimism, like excessive optimism, is wrong, and the similarity is merely the structure. This is a flawed diagnosis.

In general, behavioral explanations cover so many scenarios—optimism, pessimism—one has to have a specific behavioral insight to make an reasonable argument. Otherwise, you are like someone in favor of a 'third party' as an alternative to our two-party system, a group with less in common among itself than with the parties it is an alternative to.

Sunday, July 26, 2009

Not quite Michiko Kakutani, but someone finally thoughtfully reviewed my book. Aaron Brown blogs a lot over at the Wilmott general forum, and he's the kind of practitioner I was hoping to reach: a practitioner who understands financial mathematics. Given his other reviews on Amazon, we don't have a lot in common: he likes poker (which I find boring), and he likes a lot of books I don't. He wrote a neat book, the Poker Face of Wall Street, about how our innate desire to gamble leads to all sorts of markets, even financing. He has a rather long review over at Amazon. While he gave it a mixed review (3 out of 5 stars), I take pride in that all his other reviews are "5" or "1", which means I made him think. I think the positives he mentions are objectively more positive than the negatives--I'd rather be sloppy but make an important novel point, than not have such a point but write with precision and verve. As my book doesn't get a thoughtful review very often, I want to address his criticisms:

First, he notes the following typo:

An example of the sloppiness (and there are many) is on page 21, "The key to the portfolio approach is the variance of two random variables is less than the sum of their variance." This makes no sense. He might mean "The variance of THE SUM of two random variables is less than the sum of their variances,"

Alas, he is exactly right. I meant 'variance of the sum' but wrote 'sum of the variances'. A classic brain fart, like writing 'the wet was water', a phrase one's brain turns into 'the water was wet' when you read it 50 times because that's what brains do, and reading it over and over makes it even harder to see.

Fundamentally, there was only light editing of my work. I recognize that meticulousness is not one of my strong points, and should have paid for extra editing, but I was grateful to Wiley for publishing my book, and so took what I got. As the list of acknowledgements will attests (ie, none), this book did not benefit from extensive vetting. There are about 5 such mistakes, and as to whether this is 'many' is a matter of perspective. Yet in context generally it was obvious as to what is meant. For example, in this case it was right above a graph that shows that portfolio variance declines as a function of portfolio size, and talk about how diversification lowers risk. But I can sympathize that such mistakes are distracting.

Brown also bemoans the $95 price. Gee, I didn't know anyone would pay that much. Amazon sells it for about $60, and the 'used' copies are basically new copies released to small stores that are selling it, and these go down to $52. Nevertheless, it is above the usual $20 to $30 one is used to paying for books, but it's a niche, and books with math usually have sufficiently small audiences that such is the price. I would have liked to sell a $30 book so it could be at Barnes and Noble, but it's a rather specific, technical arguement with a limited audience.

A final criticism was that I "Lack of appreciation for other people's thought", and he specifically mentions Taleb. Alas, I have Taleb fatigue and consider him a lightweight blowhard, not The Establishment I am criticizing (represented by, say, Fama, French, Cochrane, Campbell, Harvey, Schwert, etc.). In a sense, like Taleb, I am criticizing the Establishment, but we have as much in common as typical third party candidates. Considering that Taleb's main empirical points are about fat tails and peso problems, these are standard problems and are addressed through the extant, large literature, that exists independent of Taleb.

But in general, I think I amply provide references to earlier research, and for almost every empirical point provide specific papers. My novelty, empirically, is highlighting that the scope of data suggest a flat risk-return relation in general; each individual finding, such as within equities, or currencies, points to literature in that domain, literature that is often quite deep.

Brown states:

The book's summary of quantitative finance is backed up by lots of references, but I would bet that the author has not read all the references. He doesn't even seem to be familiar with Hyman Minksky's work, and he was a graduate assistant for Minsky.

Actually, I have thoroughly read all my references, and I do appreciate Minsky's work (I was his TA as an undergrad, not grad), and noted the Minskian notion of Keynesian uncertainty was not fruitful because metrics of uncertainty, emprically, are not positively related to returns (eg, IPOs, or firms with relatively high amounts of analyst forecast dispersion, have lower returns than average).

Brown then states

And "expected return" only makes sense in a rigorous context (who does the "expecting," and when?). The author scorns rigor, but then uses the concept of expected return in a model with divergent expectations among investors, without discussion of whose beliefs define the expected return, and fails to distinguish that concept clearly from ex post average return and market-clearing return.

I don't make a distinction between long and short term expectations, and most asset pricing models are simple one-period models. In many cases, one can find short and long term expectations have different properties unless returns have certain distributions, or utility functions have specific functional forms, and generally these discussions lead to hair splitting, and generally add little insight. Thus, like almost everyone in this space I found this distinction an uninteresting complication. More fundamentally, expected returns should equal average returns over large enough sample, just as a sample mean converges to the population mean over time. That so many assets show sample means in direct contrast to theory implies to many of Finance's founding fathers that 'expected returns' are hard to measure, but after 50 years I find this rather uncompelling.

But let's get on to the good things he had to say, after all, it was 3 stars, not 1!

What I like about this book: * It contains important new ideas that can help any risk-taker with quantitative skills succeed * It challenges conventional wisdom * The meat of the book is based on practical experience, not just things that seem right to the author, but things he has tried, and generally with success

Those are good things, I think, and highlight in make a new point about something important, with a practical slant. I think for $52, even with typos, that makes it a good buy.

Brown ends with

This idea is integrated into a reasonably complete financial theory. The foundation seems solid but, as described above, its superstructure is jumbled and ugly.

The ugliness? I too dislike ugliness. I did not want the book to be too technical, however, so my fundamental model is a bit incomplete in the book, but the gist is rather simple:

Payoffs to Assets X and Y in States 1 and 2

Total Return

Relative Return

X

Y

Avg

X

Y

state 1

0

-20

-10

+10

-10

state 2

20

40

30

-10

+10

As shown in the table above, Y is usually considered riskier, with a 60 point range in payoffs versus a 20 point range for X. Yet on a relative basis, each asset generates identical risk. Everything follows from that. The proof of this is rather straightforward, and I outline several models of varying degrees of elegance in this SSRN paper here. But that's the big idea in a simple nutshell, and I don't find such a simple model ugly.

Wednesday, July 22, 2009

Nassim Taleb has become popular, though I don't think he has anything really profound to say (see my book review here). Indeed, a reviewer of my book Finding Alpha lamented I did not mention Taleb, but I did not see the point because I was making a serious point about asset pricing theory and Taleb is a pedestrian populizer, who like all popular populizers, is successful at convincing a lot of people he is saying something new and true. This is not the same as actually saying something new and true. His book does not add any new data, or theoretical insight, to this corpus of knowledge (e.g., the Rietz-Barro Peso problem). But as funds affiliated with Taleb are becoming popular I think it would be helpful to address those specific strategies. The basic premise is that financial economists, and investors, systematically neglect improbable events. The result is that out-of-the-money options, especially qualitative analogues like unconventional investment ideas picked up at cocktail parties, offer the best reward-to-risk ratio. Let's consider these.

You can invest in a Black Swan fund that buys out-of-the-money options such as Universa Investments run by his former partner Mark Spitznagel. Taleb, and Spitznagel, would argue their implementation is much more sophisticated than merely buying out-of-the-money options in that it also takes advantage of 'behavioral biases'. Now, as 'prospect theory' implies people ignore, or overweight, improbable events, such 'behavioral biases' allow a strategy a great deal of latitude. In practice simple ideas, such as the underpricing of out-of-the-money options is too simple to sell, so the vendor feels compelled to confabulate a pretentious but useless tweak. In this case, that just means one sells in-the-money options to lighten the expense (more gamma, less vega). Do the math, and this strategy simply shifts your payoff distribution so it has a funky nonlinearity, shifting returns from the [-10%,0] space to the [-∞,-10%] and [0,∞] space, but the same expected return. That is, say you buy $2 worth of out of the money put options, and offset this a little by selling $1 worth of in-the-money put options. This means you still hit a home run in the extreme event like 2008 (which was, statistically, improbable); you make less in the more probable adverse event; you lose less if the market rises. As empirical studies have found option returns to decrease as one goes out of the money (see Ni, or Bondarenko, or Coval and Shumway), the in-the-money vol sold is relatively underpriced, so the only behavioral bias this is leveraging is a marketing one. Considering that out-of-the-money options are most overpriced, this is a bad strategy.

Clearly in big moves such as 2008 this strategy outperforms. Yet on average, I doubt it. That is, much was made of the "65% to 115%" return reported in October of some Black Swan Funds (see WSJ here), but the VIX peaked then at 80, and is now at 23, while the market has rebounded. It would be interesting to know the subsequent returns, but everyone merely quotes the hearsay (always, 'a person close to the fund reported...') reported on their top tic. As Taleb is insistent that too many investors naively chase last year's winners, it would only be consistent to not make too much of one year's returns. Indeed, Empirica Kurtosis, his earlier hedge fund, also started out with a widely reported 60% return in 2000, but then folded quietly in 2004. I earlier said I would donate $10k USD to his favorite charity if he sends me audited financials showing the cumulative Sharpe ratio of Empirica Kurtosis LLP over its lifetime was greater than 0.5 (which is a poor hedge fund return, consistent with exit), and the offer still stands. Thus, over the long run, not a sequence of 2008s, this is a crappy strategy.

The other problem with out-of-the-money strategies is that option market makers hate being naked low-delta options. You don't have to buy too many to move the price, implying market impact is high. This makes these strategies even more expensive than any simulation when done in size. That doesn't bode well for these now-popular strategies.

Another claim by Taleb is that 'wild' risks from cocktail party chatter is especially useful. At some level this is like saying things that can't be quantified are really important, which has the nice property of being tautologically untestable, but in practice we understand what this means: funky investments outside of stocks, bonds, bank deposits, etc. Llama farms, gold medallions, and no-money-down real estate, are all unconventional, and all scams. Sure, the people pitching them show someone who got rich doing this, the same way Amway lines up its multilevel marketing operation, it is an appealing idea—why not me? Airport Holiday Inn conference rooms are always full of conferences on how to become rich following their 3-point plan, which invariably involves trading through them, or buying their $100 instruction manual. They have a horrible average return, because 'fraudulent scam' is not rare in this space, rather de rigueur. Staffcentrix offers advice and due diligence on home-based businesses offered on the internet. A principal there, Christine Durst, states that the ratios of scams to real home-based businesses is 54-1 on the internet, most following the plan of selling a modestly priced but useless information brochure, enough to make money, not enough to elicit a lawsuit. But the bottom line is that virtual out-of-the-money options are, if anything, more expensive than those traded on exchanges.

In my book Finding Alpha, I argue that people tend to pay for hope, and nothing offers hope better than the lottery-like returns available in potential Black Swans. Hope is a good thing, and motivates a lot of hard work and creativity. But it would be foolish to think that the more improbable, the more speculative, the more derided by economists, the better the risk-adjusted return merely because of this. This tendency to buy into lottery ticket leads to all sorts of really bad investments:

sports longshots such as 50-1 odds horses, have lower returns than favorites

lotteries with the highest payouts have the lowest expected returns

IPOs have lower-than-average stock returns

[This is in my book, and also summarized on an SSRN paper I wrote here.] Notice a pattern? The more volatile, more uncertain, the lower the return. People pay a premium (accept a lower return) for 'Black Swans', because in one fell swoop, they can get rich and prove they were RIGHT! Instant satisfaction. Plus, if you really have the touch, why waste time choosing Coke over Pepsi, when you can choose between GM and Citi!

Basically one would be better off not chasing dreams via Black Swans, and stick to boring investments. Finding alpha—a risk-adjusted return premium—is very difficult, and it involves a niche specific to an individual's skills, which almost surely is not in investing anymore than the average person has alpha singing or writing romance novels. Black Swan investing is a sucker's game, endemic in markets, a perennial loser, and highlights asset classes to avoid, not pursue.

Shocking? Not really. If we assume a 50-50 chance of rising, we should expect this to occur once every ten years, and it did not happen in the prior ten. Below is the actual frequency of 'runs' (consecutive trending), compared to the 50-50 theoretical (actual markets go up 52% of days, but that's not material here).

James Taranto notes the latest kerfluffle about Henry Louis Gates getting arrested for Breaking and Entering, as a neigbor saw him breaking into his own house (the door was jammed). The Boston Globe notes the following thoughts from Gates's Harvard colleague:

“He and I both raised the question of if he had been a white professor, whether this kind of thing would have happened to him, that they arrested him without any corroborating evidence,” said S. Allen Counter, a Harvard Medical School professor who spoke with Gates about the incident Friday. “I am deeply concerned about the way he was treated, and called him to express my deepest sadness and sympathy.”

Counter, who had called Gates from the Nobel Institute in Sweden, where Counter is on sabbatical, said that Gates was “shaken” and “horrified” by his arrest.

Deeply concerned? Shaken? Horrified? Look at the picture above (taken from the Wash Post), and you can imagine the scene (love the look on the black cop's face, the hand raised, the open mouth on Gates saying you have "no idea who [you're] was messing with!"). He has an interview on The Root talking about his 'terrible and humiliating' experience.

I remember having blown a bike tire in grad school I walked my bike tire to the bike shop across campus. I was an instructor at Northwestern at the time, and there were many bikes around campus and nearby, along with many bicycle thiefs (alas, my best bike ever was stolen there). Now, holding merely a bike tire looks suspicious because many bikes are locked up in a way that you can easily remove the tire. Anyway, cops saw me, and gave me the run-down: where was I going? where did I get the bike tire? where did I live? Where did I work? They called in all this information, and it took about 15 minutes to verify I was an instructor at the University. Finally I was allow on my merry way. There was no apology received, or asked. They weren't mean, but they weren't very nice either.

I've had several such run ins. I figure many cops are jerks because it appeals to people who like to boss others around. But it's an essential job, and if we had a bunch of sociologists or peace activists on the police force there would be anarchy, which only helps non-uniformed oppressors.

As someone who had liberal parents growing up in Southern California, I have never been racist, so I have no racial guilt. I think everyone should be treated the same, which is why I find these cases so repellent. Obama is not making these incidents go away, just as electing black mayors did not reduce the claims of racism in the cities where this occurred. I suspect many whites thought that by electing a black president, perhaps black/white relations in America will turn the corner, as the black community would see this as evidence that the white majority is not racist and assimilate like the Germans, Irish and Italians. I was born around a year after the Civil Rights Act was signed and my parents remember driving through the 1965 Watts riots to the hospital. As a child my parents were rather optimistic as if black/white would be like Lutheran/Methodist, a distinction without any resonance today. But things aren't getting better in general, and I'm not optimistic.

This is classic difference between a conservative and a liberal on questions of commerce. A liberal thinks that governments can be more efficient if we set up top-down councils that issue wise edicts; a conservative thinks such committees will not issue any wise edicts [note, on social policies this is reversed, and here I side with the liberals]. I would admit most such councils are filled with people of good faith, but their task is futile, because they don't have the information to make such decisions, nor the incentives to make trade-offs implicit in any wise decisions.

This all reminds me of when I worked in large corporations, and we would form big committees on the 54th floor to get rid of waste. Unless there's a specific plan, which inevitably has winners and losers, such a committee is merely a refuge for grandstanding and a waste of bagels. All large government agencies (the Post Office, the Department of Defense, Education Boards) have 'best practices' committees, 'effectiveness councils', with various other names. They all come to naught because the bottom line incentives are not conducive to cost cutting. They are fundamentally spending other people's money on other people, without any direct, strong incentive to do so efficiently. The incentive to cut costs gets lost in the context of fairness, justice, and coalition building.

Is there an example of a government committee, like the 'comparative effictiveness review', that has ever cut costs? A wise government council that has identified best practices more efficiently than a market? Government purchasers actually finding lower cost providers? Is there insufficient incentive to 'cut costs' currently, compared to the new system?

The only way to cut costs is to force those demanding services to economize by decentralize decision making, in the process exposing health care demand to the costs of more of their decisions. Currently, about 10% of health care expenditures are out-of-pocket, and when someone else pays, people ask for too much, suppliers inflate costs, and here we are. But current legislation is all about benefits and almost painless cost cuts that involve no inconvenience to the rabble. This is why free marketers like myself and Mankiw are pessimistic.

You might as well put your faith in input-output matrices, dynamic programming, or mandatory readings from "Who Moved My Cheese?" There are two ways to cut health care costs. Have government decide to spend at most $X on health care, and have their wise committees figure out how to deal with this lower budget, or increase the out-of-pocket expenditures of people so they internalize their costs and economize on health care purchases.

Monday, July 20, 2009

Attorney General Andrew Cuomo warned that his office plans to sue the largest online brokerage firm for civil fraud over its marketing and sales of auction-rate securities to clients.

Cuomo is also going after the ratings agencies, along with many others, for basically rating securities as AAA when they subsequently many such securities, primarily MBS related to housing, defaulted. A AAA rating has a 0.03% ish annualized probability of default. My problem is that this is a mistake, not criminal. While Moody's may have been overly incented to rate these securities highly, such an incentive has existed since the beginnings of the industry, and many other failed rating agencies neglected this at their peril (remember Duff & Phelps?). So, it's a standard incentive problem that I don't think is helped by piling on after the fact.

By itself it would not be so bad, it's just that going after brokers for selling AAA securities because they turned out riskier than expected means that now the rating agencies, and brokers, have to 'underwrite' (ie, evaluate and due thorough analysis) the same securities. It is a fact that the senior piece of some capital investment will have a low probability of default, due to the value of the underlying business. For example, if you lend someone $100k to buy a house, and the house has an independent appraisal of $300k, the probability you will lose any money on that $100k is very small; for a large portfolio, basically absent. To now say that everything must be evaluated by everyone just creates waste, because the costs are too great, the benefits too small. Remember, a growing economy comes from doing more with less, and a large part of this is in information processing. We take for granted real GDP growth, but improved financial efficiency—innovation!—is part of that. The only way to guarantee no more blow ups is to guarantee no more growth, a poor bargain (Gillian Tett's book Fool's Gold seems to think innovation is something to be discouraged).

There should be a vibrant sector of 'informationally insensitive' assets that have minuscule default rates. Such assets will be hypothecated by banks when deposited as collateral, making them effectively part of the monetary base. It's unavoidable, in the same way factional reserve banking is unavoidable.

I hope they remember that the Fed and all the regulators considered mortgages low risk because of their historical track record, which had minor losses in aggregate. No asset class has back-to-back surprises, so doubling down on mortgages is rather ahistorical from that perspective. Remember Commercial Real Estate? After its vicious 1990 cycle, default were historically low for the next 15 years (lot's of concern now, to be sure, however). Better to focus on other assets that have historically been safest. Why not raise the risk levels for municipal bonds, state bonds, even US government bonds? Clearly these have a potential for massive failure in spite of their golden track record. After all, many banks defaulted after the panic of 1838, surprising the Europeans who thought this unimaginable after they seemed so strong during the earlier panic of 1819. But that would cut into the incentives of the regulators, not rich bankers (all 'bankers' are now caricatured as Goldman Sachs employees making $700k/year).

Sunday, July 19, 2009

Office 2007 is an abomination, with defaults in every app seemingly all set to 'Annoy Eric'. But here's Bill Gates doing good work. He put a bunch of Feynman videos online from 1964. Thanks Bill. You need to watch this using IE (of course).

Funny but devastating aside on Bob Wright' new book, The Evolution of God, in that it isn't clear whether or not Bob believes religion is net good, which is a rather important point in summing up religion. That is, if you look at the 10,000 year development of religion, and see both sides of that argument, did you really see anything?:

It reminds me of Brad DeLong's criticim of Skidelisky's 3-part biography of Keynes, which he said was excellent, except for where Skidelsky's writings on post WW2 economics, which basically means it's a fun read about trivialities. Skidelsky took exception, and DeLong was puzzled, because he emphasized he did like the book, but one does not spend a decade writing a 3-volume set that is irrelevant to the main point (here, current economic science).

Every writer likes having their book called a 'good read', and most readers really leave it there, but if it also wrong on its main assertion, or does not really have a point, this is a Pyrrhic victory.

Friday, July 17, 2009

the risk to the government from a potential default on GSE [Fannie Mae] debt is effectively zero...the expected cost to the government of providing an explicit government guarantee on $1 trillion in GSE debt is just $2 million.

The main cause of the crisis was the behavior of the banks—largely a result of misguided incentives unrestrained by good regulation. Conservative ideology, along with unrealistic economic models of perfect information, perfect competition, and perfect markets, fostered lax regulation, and campaign contributions helped the political process along. The banks misjudged risk, wildly overleveraged, and paid their executives handsomely for being short-sighted; lax regulation let them get away with it—putting at risk the entire economy. The mortgage brokers neglected due diligence, since they would not bear the risk of default once their mortgages had been securitized and sold to others. Others can be blamed: the ratings agencies that judged subprime securities as investment grade; the Fed, which contributed low interest rates; the Bush administration, whose Iraq war and tax cuts for the rich made low interest rates necessary.

Thursday, July 16, 2009

With Danny Kahneman's Nobel prize in economics every other week has a big-name author or journalist writing a breathless article about how the new 'behavioral economics' will fix sterile financial theory. Alas, way back in 1951 this was a tired theme. George Stigler noted "each decade, for the past nine or ten decades [ie, back to 1851!], economists have read widely in the then-current psychological literature. These explorers have published their findings, and others in the field have found them wanting—wanting in useful hypotheses about economic behavior."

Take, for example, the anchoring bias, where people do not adjust their prior beliefs sufficiently when presented with new data. On the other hand, there's the case where people do not sufficiently account for base rate information, as for example when they are told a woman is quiet and assume she's a librarian, not saleswoman, even though there are more saleswomen than librarians. Thus, over, or underreaction to information is a common 'bias', and so Kahneman's classic work Judgment Under Uncertainty: Heuristics and Biases surveys papers from the 1970s! After a generation, the low hanging fruit has been picked, and where are we? Momentum and mean-reversion are part of the 'new' finance, and George Soros proudly notes that his theory of markets has markets biased—though it could be in either direction. Yet, these are not really discovered by behavioral economics, but explained by it on a case by case basis. Prospect theory teaches us that people overweight, or underweight, extreme observations in various contexts. These insights are no more useful than saying the effect of X on Y 'could go either way, depending on a bunch of other information we probably won't notice until after the fact'.

A new book about psychiatry, Doctoring the Mind by Richard Bentall argues that the science of the mind is hardly a successful science. He argues that mental illness is on the increase and sufferers in the developed world with access to psychiatric care actually fare worse than patients in poorer countries. It wasn't too long ago, many psychologists thought a lot of anxiety came from wanting to kill one's father in order to have sex with one's mother, an ambition so absurd only a scientist could think it made sense. Then there were lobotomies, homosexuality as a mental illness, criminals having insufficient self esteem (we now know they have too much), autism caused by bad mothering, and on and on. Lastly, have you ever thought that psychologists are happier, more well adjusted people than average? I don't think so, yet that's their specialty. So these guys are now going to help economics? I doubt it.

This is not to say I think economics is especially fruitful. My book addresses a rather central issue that I think is flawed in economics. I'm just saying that 'cognitive biases' are an embarrassment of riches that lead everywhere and nowhere, which Bentall's books suggests is hardly surprising.

Wednesday, July 15, 2009

Recently, my email has been full of all sorts of Cramer-Spam, with stories about all these great stock picks he made. Here's a sample of bullet points from emails from "Jim Cramer (members@e.mail-thestreet.com)":

Model Portfolio Outperforms S&P 500: 134.79% Total Average Return*

On January 20th, I bought Goldman Sachs at $60. When it hit $85 on January 28th, I trimmed my shares, locking in a 41% gain

I bought GE at $8.78 when everyone thought it was going bankrupt — and now it's up 50%.

My subscribers were right on hand as I bought NKE for $44 on March 19th, watched the stock skyrocket, and pocketed my profits on June 2nd for a return of 34%.

RealMoney recommended China Green Agriculture (CGA) when its shares were trading at $5. The stock closed at $8.09 and subscribers who followed our advice netted a 61.8% gain

RealMoney advised subscribers to buy shares in Darling International (DAR) when the stock was trading at $4.54 a share. The stock then closed at $6.60. Once again, RealMoney nailed the market with a 46% return.

P.S. I can only extend this offer to you for 48 hours so please do not delay.... you have absolutely nothing to lose when you take us up on our $129.95 offer

Notice his example picks have an average return well above anyone's hurdle rate, with returns of 30% to 134.79% (love than .79). It's funny when people sell penis enlargement pills online for $50 because its silly and not a lot of money, but as John Stewart noted, the stock market isn't a game. This is disgraceful and CNBC should be aware this makes them part of his scam. It simply isn't plausible that 30%+ returns are representative, and they know that, and suredly would say they didn't mean every return is this high, but it's like lottery ads saying 'anyone can win'—true enough, but highly misleading.

The following is from my book on stock recommendations, where I note that in contrast to standard asset pricing theory, ALL stock recommendations promise above average returns. In theory, half of all stocks should be recommended with below-average returns because they have good 'risk adjusted' returns, but this doesn't happen. That this never happens highlights a profound mischaracterization of risk-taking by standard asset pricing theory. People only take risk to outperform, never to achieve a lower return with greater safety (excluding cash-like asset holdings, such as AAA bonds or short term paper).

Jim Cramer is now an internet hack shill. His encyclopedic knowledge of company details is impressive, and he did run a successful hedge fund for a decade, though as a hedge fund his performance claims are unaudited and implausible (24% annual returns with 1 down quarter over 10 years). Yet for some strange reason, like many famous investors, he quickly realizes it is more profitable to sell advice than invest on it. If he had anything like the edge he claims (5% out performance?), it simply makes no sense to sell this advice as opposed to invest on it, especially when you have capital to start.

So now the same company (CNBC) he used for his pump-and-dumps in the 1990s he uses to broadcast his highly popular show 'Mad Money', illustrating that the best salesman create willing dupes impervious to experience. Note that Cramer went on John Stewart's Daily Show, and instead of defending himself, obsequiously cried 'my bad' and hoped he could then buddy up with a witty and more popular celebrity. Stewart was having none of it, and just piled on the criticism, showing that some people have the integrity not to change their positions merely because they are offered a mutual public admiration quid-pro-quo.

As found in this YouTube clip, Cramer has a selective memory when it comes to his recommendations. And his bizarre claim that he manipulated the Spiders (SPY) by shorting them, is so inconceivable, it makes me skeptical of anything he says about his experience (this market is too large for someone running a small hedge fund, and after pushing it down, exactly how do you make money?).

Tuesday, July 14, 2009

Goldman Sachs is one of the most respected private firms in the world. With their astronomical paychecks, and their selective recruitment, they clearly inspire a lot of envy.

Goldman is self-interested, which means they don't share all their ideas, and they don't hire everyone capable who wants a job there, but that's inevitable and you can't let that color your views. The latest hatchet job in Rolling Stone is by Matt Tiabbi, who has a profoundly adolescent and paranoid world-view that seems clever and witty only for the kind of people who read Rolling Stone to learn about finance. It's not worth a point by point rebuttal, because like Oliver Stone's JFK, you have so many issues of contention it becomes pointless rather quickly. The bottom line is Goldman is a large investment bank, so they have connections to everyone and everything. To hold them responsible for all the conspicuous bad things and people of the past is just a logical error, like blaming 7-11 for alcoholism (they sell a lot of alcohol!).

Those who think Goldman was the prime mover in our financial mess are simply wrong, as Goldman was as guilty as everyone who did not second-guess the assumption that aggregate housing prices do not fall in nominal terms (academics, legislators, regulators, investors, home buyers, investment bankers, rating agencies—did I forget anyone?).

Recently, Goldman filed a complaint against an ex-employee, and somehow got the Justice Department to effectively act as their attorneys in what should be a civil matter! That is, when I was sued by my ex-employer for 'violating my confidentiality agreement' in various nefarious ways (such as applying mean-variance optimization), it was a civil action. A criminal action is much more difficult to defend, and is very unusual for such a charge. Clearly Goldman has connections with the right people, but everyone knows that.

I think GS as an example of what happens when you have a bunch of smart, highly connected people working together to get rich. There is a lot of inside ownership, and so their large bonus structure clearly implies they understand the Lafffer curve, in that giving people stronger incentives helps everyone—capital and labor.

In the first half of 2009 suggested an average employee compensation of $700k per year. In general, GS pays about as much in bonuses they do in profits to shareholders. This suggests those on the ground, making the deals, are able to get about half of the profit.

This is often the case for alpha generators, as for example consider that hedge funds make 2 percent of assets and 20 percent of profits. Then over the glory years of convertible bonds from 1994 through 2003 when those funds returned 10 percent to investors with minuscule volatility, the owners of these funds pulled in about 4 percent of assets in profits for themselves, while investors received about 4.5 percent in annual returns above the LIBOR. As one might expect when you have two inputs, equally necessary, the split seems to be near 50–50. That is, in any investment with alpha, you have two things, equally necessary: he who identifies the alpha, and he with the capital. In any particular case the proceeds are split according to negotiating strength, but on average we should expect an approximate equal split, as there appears to be in high alpha strategies (I go over this in my book (of course) Finding Alpha).

The net result is that if you pay these lucky bastards a lot of money, as an equity owner you can make a lot of money too. There are surely a lot of overpaid Goldman employees as you would expect in any large organization (I know several!), and much of their value comes from Goldman's alpha: connections, brandname, and monopoly access. Yet on average these people are being rewarded appropriately and if you want a growing economy you have to accept this. I know this is hard for many people to accept because given the large number of smart, hard-working individuals of good integrity who don't make $700k a year, Goldman's workers are in that sense very fortunate and this is somehow unfair. You can't run an economy based on cosmic justice—that's for our creator—so you have to deal with the reality that life is somewhat arbitrary, and to accept that inequality in income is better than poverty. Considering they make this money out of their profits, not taxes, it doesn't bother me at all.

Monday, July 13, 2009

One of the most important constants in finance is the Equity Risk premium, that expected return on the signature risk asset, equities, over the risk free alternative (usually, long-term Treasuries). It's the one risk premium that is generally considered positive, too large even, which is a relief because in most areas the returns are decidedly negative for taking more risk. Estimates in the early 1990s were about 8%, now, around 3% annually.

In today's WSJ Jason Zwieg goes over a flaw in Jeremey Siegel's famous stock return estimate going back to 1802. As one would expect, stock indices prior to 1871 have a lot of survivorship bias issues. He suspects Siegel's index accounts for only 5% of equity investments actually available, and so could be severely biased, because the difference between the winners, and the average, is usually quite large. This highlights the many subtle biases in historical asset returns.

I have found that on average industry stratistics are maintained by biased parties, because those who do the work collecting such data invariably have a vested interest in the asset class, and incentives matter. Little things like selection biases in historical reconstructions, corporate actions, can get very detailed and matter a great deal. I have seen performance records where I had inside knowledge of the guy's strategy, and every time their performance was exaggerated. People exaggerate with a rather straightforward, self-interested bias on things that can help them, and index creators invariably have a rooting interest in the asset class they are 'merely monitoring'.

Consider the following annualized adjustments that mainstream economists apply piecemeal, though when considered in total take the current estimate of 3% well below zero:

Geometric vs. Arithmetic averaging: 2% (See Dimson, Marsh, and Staunton). This is where a stock going from 100, to 200, back to 100 has an arithmetic return of +25%, the geometric lower, at zero. Geometric is relevant to the long-term investor, and most investors have a much greater volatility than the indices, making this estimate conservative.

Survivorship Bias/Peso Problems: 3% (see Rietz, Jorion and Goetzmann, Barro) The US is the best market in the 20th century, so not a good datapoint for an 'average' going forward.

Taxes: 3% (see Gannon and Blum, 2006). Since 1960, the after-tax equity premium is reduced to about 60 basis points is you assume 20% turnover and a top tax rate.

Adverse market Timing: 3% (See Dichev, 2005). Alas, most inflows are at peaks, outflows in troughs. The average dollar invested has experienced a much lower return than the annual averages.

Transaction Costs: 2%. historically, commissions were about 60 cent/share until the 1975 deregulation, and are currently w about 2 cents a share (about 0.1%) on average. Plus, mutual funds often had 8.5% fees. Trade impact is rarely mentioned, but for an institution it is unavoidable, at least 0.2% one-way. Lastly, the bid-ask spread will cost you about 0.25% on average if you cross it, much more historically. It doesn't matter than some passive funds have negative expenses, because we are talking about a hundred year average for your average or marginal investor.

The bottom line is these are all individually very modest adjustments, and so the current 3% equity risk premium is well below the total 13% adjustment. Like the OJ evidence, you can throw out ANY ¾ of the evidence and the equity premium is zero! Caveat Emptor.

(double click to go to YouTube, where you can see the second part of this video thread)

Sunday, July 12, 2009

There was an interesting paper on estimating the probability of the tails via option prices (see Backus, Chernov, and Martin here). Barro seems to have really revived the Rietz 'peso problem' model, by looking at a variety of large macro-economic shocks related to wars and revolutions in the twentieth century. There's an excellent summary of this work here.

One person noted that things could actually be pretty boring. That is, in 1987 the market fell so much on one day (23%), ever since then there has been a large premium for out-of-the-money options. The graph above is from Jackworth and Rubinstein (1994). This shows that basically the market did not anticipate the 1987 crash, but since then, has this event priced in.

The funny thing is how far back and how deep this literature on disasters is. Nassim Taleb and his acolytes (the Taleban) seem to think economists are totally wedded to the Gaussian distribution, which ignores fat tails and extreme events. That is, he sees the naive Black-Scholes model, and ignoring the volatility smile, infers that this means economists don't believe disasters matter. This is just a really ignorant and misleading statement, fun for dilettantes who love to lampoon experts via a caricature, but it is really a waste of time.

Saturday, July 11, 2009

My forecasted winners: Henderson, St.Pierre, Lesnar.[note: this was pre, and I was 100% correct!]

I actually wanted to bet on Lesnar, but on bodog.com it looked like I would have to risk $5 to make $1, which seemed too expensive. But Lesnar's a local guy, and I heard that he really trains hard, and is just a genetic freak in terms of strength. His partners said that Lesnar's ju-jitsu has improved considerably so Mir has basically no chance of surprising Lesnar with a knee bar like last year.

Too bad Frank Mir lost, he's a really thoughtful guy, unlike Lesnar, who is dumb as a post. Here's a picture of me giving Frank the business at the Arnold Classic in 2005.

On average, economists are thinner than average. I'm not sure why, or if that's good for economists. Financial economists are also about 85% male, and while most practice in the US, most are from Europe and Asi. Most importantly for me: Everyone in finance speaks English!

discussions are very honest and thorough about things like logic, innovation, and relation to the literature.

discussions are silent on irrelevancies. If you estimate something very complicated on something that 90% of he audience finds irrelevant, those 10% who find it interesting will mention ways to adjust your method. The 90% who find it irrelevant just keep their mouths shut. This encourages irrelevancies (eg, GMM, looking at various instruments)

there was a strong feeling that the Federal Reserve was in danger of losing its independence. That the Federal Government was basically lost all fiscal discipline, and so anticipating future Fed monetizations, was a common theme. If hyperinflation due to fiscal irrationality comes, it will be with a large number of those seeing it before the fact, very unlike the recent crisis where very few in 2006 warned of a housing price collapse.

There were a lot of papers about how to account for fat tail events. These were called 'nuclear' or crisis events under the Barro-Reitz framework (aka Peso problems). If you listen to Nassim Taleb you would think economists were unaware of fat tails, but if you went to this conference, you would hear a lot about what Taleb calls 'Black Swans'. This is why Taleb hates academics, because they don't see his big idea as 'new'.

Calibration exercises, which are true by definition, have too much weight. Either demonstrate out-of-sample usefulness or don't mention it. I find these totally useless empirically, but that's because my game is to make money for investors, in contrast to academics, which is to publish papers useful for future publications.

Not a bad read by the Committee on Oversight and Government Reform. It goes over how the legislative drive to increase home ownership contributed to this mess. Too bad the author(s) are simply designated as 'staff'.

“the risk to the government from a potential default on GSE debt is effectively zero,” and that “the expected cost to the government of providing an explicit government guarantee on $1 trillion in GSE debt is just $2 million."

It ends with a taste of why this won't go anywhere, noting Barney Frank has "asserted that those who criticize these policies seek to place blame for the financial crisis solely on borrowers of modest means", but then references a piece that is a bit more, uh, frank: "Frank Says GOP Housing Attacks Racially Motivated". This highlights how we got into this mess, in that the 20% down payment, or income verification criteria, was deemed racist, so indefensible.

Wednesday, July 08, 2009

The 'myth' of the rational markets suggests a straw man argument in practice, a position no one argues, but popular discussion and pandering authors discuss endlessly. If you think rationality implies perfection or an absence of market declines you are wrong, so don't waste too much time on this precious insight; it's like discovering that nature AND nurture affect IQ.

It is important to remember that while academics, almost exclusively economists, believe some form of market efficiency, most non-economists don't. Back in the 1970s and 80s when index funds were being introduced, most leading magazines lambasted the idea, noting how stupid an index fund was because people like Warren Buffet or Peter Lynch proves this is suboptimal. Thus, John Bogle (head of Vanguard) had to fight to get his board to accept an index fund, and this while he was CEO! Even today index funds are a small portion (about 15%, depending on how you count it) of equity investors.

In my book Finding Alpha (which has a short SSRN summary article here), I note that unlike Efficient Markets Hypothesis, which has never been popular with regular people, the Capital Asset Pricing Model has been warmly regarded since inception. The picture above shows the cover of Institutional Investor magazine in 1971 discussing 'The Beta Cult' as if it were a done deal. The first empirical confirmation had yet to even be published! Of course, this confirmation (by Black, Jensen and Scholes('72), Fama and MacBeth ('73), and Blume and Friend('73)) was spurious, meticulously correcting for 'errors in variables', but totally blowing it on the omitted variable of size, which itself proxied measurement error issues related to delistings.

Why does the CAPM and its derivatives get such a better reception than the Efficient Markets Hypothesis? Both rely on rational investors, though they are independent theories (neither implies the other). I think the efficient markets hypothesis plays into an easier caricature, which is unfortunate because as a guideline the implication of the EMH is a much better approximation of reality than the CAPM (or its spawn the SDF or APT approaches). That is, no measure of risk linearly, positively, relates to returns as a first approximation. In contrast, most investors lose money the more they trade, and their deviations from the market do not, on average, have alpha. See a small discussion from my video 3 on my book Finding Alpha:

So all you non-economists so self-satisfied for not believing that markets are perfect, have fun taking on idiosyncratic risk for an extra 100 basis points a year. Way to stick to those smug economists.

Tuesday, July 07, 2009

Bob Haugen has been writing about the inefficient stock market for a long time. His JFE piece (Commonality in the determinants of expected stock returns) with Nardin Baker back in 1996. His recent SSRN paper revists these themes and declares Case Closed:

This article provides conclusive evidence that the U.S. stock market is highly inefficient. ... Stunningly, the ten percent of stocks with highest expected return, in aggregate, are low risk and highly profitable, with positive trends in profitability. They are cheap relative to current earnings, cash flow, sales, and dividends. ... Undeniably, the highest expected return stocks are, collectively, highly attractive; the lowest expected return stocks are very scary - results fatal to the efficient market hypothesis. While this evidence is consistent with risk loving in the cross-section, we also present strong evidence consistent with risk aversion in the market aggregate's longitudinal behavior. These behaviors cannot simultaneously exist in an efficient market.

My book Finding Alpha is consistent with his findings. That is, firms that have low volatility, high profitability, low leverage, and just about anything correlated with 'safe' or 'not risky' tend to outperform their opposite. The standard approach is trying to find a 'risk factor' that explains why Coca-Cola type companies are riskier than GM type companies, which I think is impossible.

Yet, I find myself disagreeing with Haugen in two major areas. First, he says that he finds people are risk averse in general, because markets fall when volatility rises. This fact is true, whether one measures this using an equity implied volatility, or an contemporaneous measure of volatility (eg, those months with the highest daily vol will have the lowest returns). Yet going forward, this result does not hold. A higher implied volatility, or historical vol, does not augur higher returns. Thus, all we know is that when volatility rises, the stock market will fall. This is only consistent with risk aversion if such a fall presages a higher future return, as where the dividend forecast is the same, but the immediate price decline (and negative return) is just capitalizing this higher return. It does not work like that. You get a lower return immediately, and no higher return in the future.

Think of it this way. If you were averse to volatility, you would want an asset that would be a relative outperformer in these periods, not a relative underperformer. But those stocks with the highest covariation with volatility changes are those same crappy stocks with the lowest overall return. In sum, contemporaneous inverse correlation between volatility and returns is inconsistent with risk aversion because forward-looking volatility and return correlations are weak if not negative as well.

Given he hates market efficiency, he should jump over to my side, and see it as an equilibrium where people pay for hope. There is generally risk neutrality, with a little risk loving at the high end, and premium for cash-type assets, creating a slight bow in risk and return.

His other issue where I find myself in disagreement is his rather over-ambitious embrace of anomalies. He had a book, the Incredible January Effect, which was a big deal in the 1980s, but you can't make money off this any more, and perhaps given transaction costs you never could. That is, much of what drives historical database anomalies are thinly traded stocks that move from $1 to $1 1/8, a massing 12.5% return, annualizing to a 3150% return! As there is a power law to stock distributions, a large proportion of stocks invariably are small and untradeable, and inferences therefrom are uninteresting.

In the early 2000's, he had a model where he ran rolling regressions on 50 or so factors, and allowed these coefficients to flip around from positive to negative. Many of the 50 factors are highly correlated (profit margin, ROE, ROA), and this causes their coefficients to have the 'wrong sign', because correlated explanatory variables tend to do this. He is vague about how he computes 'profits' in his backtests, and this can be problematic if, say, you use 1994 profits for 1995 returns, considering the '1994' fiscal year ends in June 1995 for many companies, and is released with a lag of up to 3 months. It is straightforward to account for this, but unless the author notes his explicit care for these issues, one has to assume he did not do a good job. I remember seeing his 1-10 portfolios back in 2003, and they took a nasty beating that year. A couple years later I visited his website and it was like a Soviet history text with that drubbing wiped out of the historical record, presumably because a new model was now applied to the past.

In my experience, those who use a lot of correlated factors are overfitters, and this makes their back tests look great, their out-of-sample tests horrible. His 1996 paper argues for 3% monthly excess returns. His current model implies a similar level of outperformance (40% between the top and bottom decile, annualized). Fama and French's recent study of mutual funds finds out of thousands, the top outperformers were in the 5% annualized range, so proposing your long picks outperform the market by 25% is bat-shiat crazy talk. That is transparently overfit, like internet spam advertising 50%+ returns. It's a shame, because he does not need to overfit the data to make his basic point, but he overfits nonetheless, and overfitting is one of those predilections that few economists are immune to.

Monday, July 06, 2009

I saw a snippet of Justin Fox discussing his misleadingly titled book, 'The Myth of the Rational Market', and he continues to not admonish those who praise the book but haven't read it. Market Haynes summarizes the theory of efficient markets thusly:

One of the longest held economics theories is called the Efficient Markets Hypothesis, basically it says the market's always right...

That's just wrong. It is a straw man argument, like saying Republicans hate poor people, that Black-Scholes caused the failure of LTCM, or that Value-at-Risk is a panacea: only naive critics say these things.

I think Fox may realize this, but I also think it is possible that amidst all his study, he doesn't really understand the ideas in play. After all, in that same interview, his big note of a regulatory reform that might help is Glass-Steagall, which is about as related to this crisis as the deregulation of Airlines (they both involved deregulation). For in his book, he notes the failure of beta as related to the Efficient Markets Hypothesis (the EMH), but it is not clear how. I guess the nuance of the theory, how any test is a joint test of a market model and the EMH, is too subtle for either his audience, or Fox. For example, the CAPM could be true while the EMH false, and the EMH could be true and the CAPM false. So, tying the CAPM into his book is really confusing unless you explain why and how it failed.

I still like the book, which is much less tendentious than how presented in any of his TV appearances. But not as an exposition of the EMH debate, rather, as a supplement. There's good stuff in there, just don't expect to be clear on whether markets are efficient or not.

Bloomberg reports a computer programmer, Sergey Aleynikov, was arrested July 3 on arriving at the Newark, New Jersey, airport and charged with theft of trade secrets. As someone involved in intellectual property litigation, it brings back nightmares, though I am happy to say I've never been arrested.

From Bloomberg, they note that:

the proprietary code lets the firm do “sophisticated, high-speed and high-volume trades on various stock and commodities markets,” prosecutors said. The trades generate “many millions of dollars” each year, they said.

This highlights the problem with IP law. These statements sound like sufficient probable cause to a judge, but they could be a program that buys stocks based on the simplest of pairs trading algorithms. The problem is that intellectual property law in most states allows an ex-employer a very broad scope to level charges, so if someone wants to accuse you of something very vague based on the flimsiest arguments(eg, 'he planned to do mean-variance optimization as he did at our firm') they have the right. As an instrument of harassment this is much scarier than any anti-terrorist legislation, because no one cares when it is abused. The fact that while they engage in discovery (which can last years) and send and receive interogatories, searching your hard drives and emails, you cannot work for anyone because without a precise definition as to what information, code, algorithms, etc., are at issue, anyone doing business with you is taking on infinite liability. Plus, good IP lawyers cost a lot of money, and as litigation takes several years, a large firm can easily bankrupt a target. With such a prospect, a rich litigator can make the ex-employee an offer he can't refuse.

Firms who engage in such over broad litigation are invariably alpha-less because only those so insecure about how outsiders view their alpha, and how important non-principals are to their alpha, use this tactic gratuitiously. In the end, it does not work, mainly because 1) they demonstrate they believe they have little endogenous alpha, which is usually true and 2) no new alpha comes in, because those with a choice prefer to avoid such people.

In this case, I think Goldman is probably on the right side. This is because Goldman has a habit of letting ex-employees leave and prosper, as they have learned to use their ex-employee success to their advantage. They have no insecurity that people will think Goldman's alpha is from the current crop leaving to start new companies, as this has been going on for decades. Further, the person at issue is a computer programmer, not a trader or portfolio manager, and such code is often very specific (not broad concepts like 'variance' or 'cash flow'). Lastly, programmers are usually given algorithms to code; it is implausible that such workers already knew about parochial trading rules based on previous work automating account statements for Blue Cross.